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NeuralNet Studio CLIENT-SIDE ML
Idle / Ready
← Tools

âœī¸ Drawing Input Canvas

Brush:
10×10 Grid 100 Inputs
Assign Drawing to Training Dataset Click to record sample

âš™ī¸ Training Controls & Metrics

Target Iterations / Epochs 200
Learning Rate (η) 0.040
Hidden Layer Dimension Neurons
8 Nodes
12 Nodes
16 Nodes
Epoch 0
Loss (Cross-Entropy) 0.0000
Train Accuracy 0%
LOSS CURVE

đŸŽ¯ Model Inference & Predictions

⭕ Circle WINNER 0.0%
âšī¸ Square WINNER 0.0%
đŸ”ē Triangle WINNER 0.0%

⚡ Neural Network Synaptic Graph

60 FPS LIVE WEIGHTS
Positive Weight (W > 0)
Negative Weight (W < 0)
Active Neuron (a > 0.5)
Thickness = |Weight| • Hover node to inspect